[unreadable] We propose to leverage the full scope of the Atherosclerosis Risk in Communities (ARIC) study to identify genes for incident early onset coronary heart disease (CHD) and multiple other heart, lung and blood-related phenotypes. We will genotype 600 early onset (<65 years) incident CHD cases and 1,000 individuals in a cohort random sample (CRS) for 500,000 TagSNPs spanning the human genome. We will perform a combination of computer-science based and sliding window haplotype association analyses on incident CHD and rank the SNPs based on the strength of their association. Replication of these initial findings will first be done by investigating the concordance of "statistical significance and direction of effect" between the top 10,000 (approximately 2%) SNPs from ARIC and the top 10,000 SNPs from an analysis of CHD in the Framingham Heart Study. The second opportunity for replication will come from testing those concordant SNPs (estimated to be approximately 120) in a sample of 1,000 CHD cases and 1,000 controls. For those genes that consistently replicate throughout, we will investigate the ability of environmental and lifestyle measures (e.g. diet and smoking) to modify the observed relationship between genotype and phenotype (i.e. gene-environment interaction). The cohort random sample provides an ideal cost-effective opportunity for initial studies to use genome-wide association methods to identify genes for other heart, lung and blood phenotypes. Therefore, we will begin to identify genes influencing other heart, lung and blood phenotypes using the cohort random sample and the 500,000 SNP dataset. Phenotypes to be analyzed include, but are not limited to, blood pressure, lipids, body size, clotting factors, pulse rate, lung function (e.g. FEV1), and measures of subclinical atherosclerosis (carotid artery wall thickness) and arteriosclerosis in the eye. Finally, we will support further analysis and discovery by others through sharing of data (genotype and phenotype) and analysis algorithms with other scientists in a timely fashion. This project will bring together appropriate population-based samples, good phenotyping and state-of-the art analyses to identify genes influencing CHD, along with other heart, lung and blood phenotypes. Identification of these genes will improve risk prediction and shed light on novel biological pathways bridging health and diseases. [unreadable] [unreadable] [unreadable]